ABSTRACT: A new population synthesis tool has been developed which allows an
analyst to input estimated future demographic scenarios for a modeled region
and synthesize a population from base-year survey data based on those
demographic changes. In addition, various data transferability models have
been estimated to enable the transference of a collection of travel demand
indicators from a source to a target population. The combination of the
synthetic population with transferred travel demand indicators will allow
for an impact of potential transportation impacts of estimated demographic
changes without running a complete travel demand model.

For this work, several future scenarios for the Chicago region were
estimated based on the 2030 Chicago Regional Forecast demographic estimates.
Various scenarios were created based on the more general scenario presented
in this forecast estimate, to estimate how changes would be distributed
geographically, and to estimate changes to demographic variables not
considered in the Regional Forecast. A synthetic population was then
generated using the 2000 census data for the region and updated using the
various assumed scenarios. A set of travel demand indicator data
transference models was then applied to each population. The travel data
transference models are a series of models estimated using the 2000 NHTS
data, which determine a series of travel indicators, such as average travel
distance, number of trips per day, trips per day by mode, etc. These models
can then be applied to the synthesized populations, to generate forecast
travel indicators for the region. For each future scenario, the impacts of
the assumed demographic changes in terms of travel demand are evaluated,
against the baseline travel indicators.

BIOGRAPHY

Josh is a PhD student in the department of Civil and Materials Engineering at the University of Illinois at Chicago (UIC). His primary research interest is in the field of travel demand modeling, specifically focusing on activity-based modeling approaches. He received his B.S. from the University of Illinois at Urbana-Champaign (UIUC) in 2002 and his M.S. from UIC in 2007.

His current research focuses on activity-based modeling using a behavioral process-based approach. This involves collecting and analyzing activity-scheduling and travel information to understand the underlying decision processes and integrating these processes into the full travel demand model. His advisors are Dr. Abolfazl (Kouros) Mohammadian (Civil and Materials Engineering) and Dr. Peter Nelson (Computer Science).